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Replacing missing values in data analysis by estimating values from the available data.
Graphic depiction of a bivariate distribution.
Consists of editing, coding, data entry, and data cleaning.
The middle value in a distribution.
The numerical difference between an observed value and the value predicted by the regression line.
Documentation for a data file that usually contains the question wording and responses codes for each variable.
The most commonly used statistical measure of variation.
The value or category in a distribution with the highest frequency.
A cleaning technique that can be programmed for automatic detection in computer-assisted interviewing.
Examples are Cramer’s phi and the correlation coefficient.
A graphic display of a univariate distribution.
Indicates how much the dependent variable changes for every one-unit increase in the independent variable.